What is cell phone eHealth?

wirelessguideMobile - Wireless

Nov 24, 2013 (3 years and 7 months ago)

131 views

What is cell phone eHealth?


Jeffery Loo


Abstract

This literature review examines cell phone eHealth.


It starts by defining eHealth and

exploring general definitions
as well as

the types of
technologies used.
Internet applications
were

the first insta
ntiation of eHealth and
will be
briefly
explored



in addition
,

many of the issues surrounding
the Internet also exist

for cell phones.


Afterwards, the
types

of cell phone eHealth
services available
are

outlined

in a review of

current
research studies

o
n this technology
.

Issues surrounding the development of cell phone eHealth
are then examined.


Finally, research gaps and
needs

are identified along with suggested areas for future
exploration.


Table of Contents

1.

Introduction

................................
................................
................................
.........................

2

2.

What is eHealth?

................................
................................
................................
................

2

3.

Types of eHealth technologies

................................
................................
............................

4

4.

Prevalence and promotion of eHealth

................................
................................
.................

4

5.

Advantages of eHealth

................................
................................
................................
........

6

5.1.

General advantages of inf
ormation and communication technology for eHealth

.........

6

5.2.

Advantages of the Internet for eHealth

................................
................................
.......

7

5.3.

Advantages of cell phones

for eHealth

................................
................................
.......

8

6.

Disadvantages of eHealth

................................
................................
................................
...

9

6.1.

Disadvantages of general information and communication technology for eHealth

.....

9

6.2.

Disadvantages of cell phones for eHealth

................................
................................
...

9

7.

The body of eHealth research

................................
................................
............................
10

7.1.

Overview of the eHealth research base

................................
................................
.....
10

7.2.

Evaluating the technology medium

................................
................................
............
11

7.3.

Usage
-
based eva
luation

................................
................................
............................
11

7.4.

Evidence for eHealth efficacy

................................
................................
....................
13

8.

Types of eHealth functions possible with information and communication techn
ologies

.....
14

9.

Types of cell phone eHealth services currently provided

................................
....................
15

9.1.

Review of cell phone eHealth research

................................
................................
......
16

9.2.

Images of cell phone eHealth applications

................................
................................
.
27

9.2.1.

Behavior change


physical activity

................................
................................
...
27

9.2.2.

Data collection, data analysis and health information


asthma

.........................
28

9.2.3.

Self
-
management/monitoring


asthma

................................
..............................
29

9.2.4.

Self
-
management/monitoring


diabetes and hypertension

................................
31

9.2.5.

Self
-
management/monitoring


weight management

................................
.........
31

2


9.2.6.

Monitoring by health professional and data collection


cancer

..........................
32

9.2.7.

Medical administration


appointment making

................................
....................
32

9.2.8.

Medication management

................................
................................
....................
33

9.2.9.

Diagnosis and teleconsulting


skin cancer

................................
........................
34

10.

Issues surrounding cell phone eH
ealth

................................
................................
..........
35

10.1.

Mobile healthcare

................................
................................
................................
......
35

10.2.

Technology divide

................................
................................
................................
......
35

1
0.3.

Health disparities and eHealth

................................
................................
...................
35

10.4.

eHealth literacy

................................
................................
................................
..........
36

11.

Future research

................................
................................
................................
.............
37

12.

References

................................
................................
................................
....................
39


1.

Introduction

Cell phone eHealth

(
the use of
cell phones
to deliver
healthcare services
)

is a relatively new
field.
According to a keyword search in PubMed,

eHealth
” did not appear

in the research
literature until 2000.


W
hile
the research
remains
in its infancy
,
there is
a
great
deal of
optimism for the cell phone’s
healthcare potential.
The convenience, connectivity and simple computing power of the
technology have been recognize
d by health r
esearchers
and professionals alike
.


T
his literature
introduces

cell phone eHealth
.
It does not intend

to be
an
exhaustive

review
.
M
aking

generalizations
about an emerging
field

is difficult when
much of the research
remains
at the pilot or
feasibility phase
, with few controlled studies on outcomes
(Kaplan, 2006).


S
pecific objectives are to:

1.

define

eHealth

and its
functions

2.

examine the advantages and disadvantages of eHealth

3.

o
utline the
cell phone eHealth services available

4.

examine
implicati
ons and issues
surrounding the

technology

5.

provide an overview of the research base and research needs


Internet applications for health services will be
briefly
discussed alongside the cell phone.
Examining the Internet is a natural lead to cell phone eHe
alth, since the Internet was one of the
first instantiations of “eHealth” and many of its issues relate to the cell phone.

2.

What is eHealth?

eHealth falls under the umbre
lla term of medical informatics. According to the
MeSH
Thesaurus,
medical informatics
is
“the field of information science concerned with the analysis
and dissemination of medical data through the application of computers to various aspects of
health care and medicine”
(
2007). Researchers have argued that medical informatics is not
only ab
out technology, but should focus on understanding people and new models of care
(Wyatt and Sullivan, 2005).


There are multiple definitions for eHealth
. In a systematic review of the literature up to 2004, 51
unique definitions were found (Oh et al., 2005
).

3



Two succinct
definitions

encapsulate

the breadth of definitions:


e
-
health is the use of emerging information and communications
technology, especially the Internet, to improve
or enable he
alth
and healthcare (Eng, 2001
).


e
-
health is an emerging field

of medical informatics, referring to
the organization and delivery of health services and information
using the Internet and related technologies. In a broader sense,
the term characterizes not only a technical development, but also
a new way of working,
an attitude, and a commitment for
networked, global thinking, to improve health care locally,
regionally, and worldwide by using information and communication
technology (adapted from Eysenbach 2001 cited in Pagliari et al.,
2005)
.


Purported functions

tha
t eHealth may support include: “dissemination of health
-
related
information, storage and exchange of clinical data, interprofessional communication, computer
-
based support, patient
-
provider interaction and service delivery, education, health service
manage
ment, health communities, and telemedicine, among others” (Pagliari et al., 2005).


eHealth differs from telemedicine
. Whereas telemedicine is the delivery of health care and
sharing of medical knowledge over a distance using telecommunications (
Kundu and

Sarangi,
2004 cited in Kaplan, 2006
); it differs because it
involves “a health professional at one or both
ends of the communication” (Wyatt and Sullivan, 2005).


From the varied eHealth definitions,
general themes

have been identified
for this field
(Pag
liari
et al., 2005)
:



Electronic communication through networked digital information and
communications technology, primarily the Internet
.



Differs from medical informatics, which encompasses fixed technologies
(e.g., X
-
ray equipment, diagnostic tools) and
pure bioinformatics
r
esearch.



Includes a variety of stakeholders, such as: providers, patients, citizens,
organizations, managers, academics and policymakers. In Europe, more
inclusive models are available, in contrast to the USA, where “bottom
-
up”
healt
h systems and cultures are possibly more prominent

(
Detmer, 2005
cited in Pagliari, 2005
)
.



Marked by a sense of optimism, with a focus on its benefits, potential and
rapid evolution.

For instance, the 58
th

World Health Assembly (of the
World Health Organi
zation) has passed t
he resolution regarding eHealth,

WHA 58.28
,

reco
gnizing

its potential
for
health
-
care delivery, public
health, research and health
-
related activities for the benefit of both low
-

and high
-
income countries and encourages the development

of eHealth
applications (
http://www.who.int/gb/ebwha/pdf_files/WHA58/WHA58_28
-
en.pdf
).

4




Represents a change to more patient
-
oriented and effective healthcare
system
s
,
and
including a new way of thinking.

As Kaplan (2006) notes:
eHealth is “both a structur
e and […] a way of thinking about the
integration of health services and information using the Internet and
related technologies”.


Conceptual models

that
define eHealth are
also
available.

They include:



5 C’s, which examines eHealth functions and capabil
ities and constitutes: content,
connectivity, community, commerce and care (Eng, 2001);



10 essential E’s, which identifies important values and characteristics for eHealth and
includes:
e
fficiency, enhancing quality, evidence based, empowerment, encouragem
ent,
education, enabling, extending, ethics,
and
equity

(
Eysenbach, 2001
);



a
4
-
pillar model

that includes: clinical applications, healthcare professional continuing
education, public health information, and education and lifetime health plan (Richardson,
2
003 cited in Pagliari et al., 2005).


3.

Types of
eHealth

technologies

eHealth may use a variety of information and communication technologies for service
deployment. Emerging technologies are especially promising, with the following identified for its
poten
tial impact on healthcare: satellite communications, wireless networks, palmtop
technologies, new mobile telephones, Digital TV, the WWW, virtual reality, nanotechnology and
the intersection of bioinformatics and health informatics (Pagliari et al., 2005).


An important feature of these technologies is automation and personalization.

An important
example of this is the personal agent.
This is a general term for software that represents the
individual on different types of computers, such as handheld compu
ters, personal computers
and cell phones (Wyatt and Sullivan, 2005). With personal agents, health records and
information could be personalized, stored and shared in an electronic environment.


eHealth have been conceptualized
for
wearable and portable ha
rdware.
Known as personal
health management systems, PHMSs connect individuals to computerized health information
networks (Gatzoulis and Iakovidis, 2007
; Koch, 2006
). These technologies could continuously
detect and monitor vital signs of the wearer and

then communicate measurements to health
information systems.

4.

Prevalence and promotion of

eHealth

A number of factors are driving eHealth services and their demand (as
identified

by Wyatt and
Sullivan, 2005):



Consumer forces
: increasingly consumers are dem
anding personalization of information
and services, where and when it is convenient to them. In addition, eHealth may be a
democratizing force, as citizens communicate with their physicians and other patients
more freely.



Changes in the healthcare system
:

eHealth may address staff shortage
and personnel
issues, as automated,
tele
-
outsourced
, or home
-
based

services are provided. In
addition, eHealth may reallocate some health service costs to the consumer
.
Consumer
-
oriented resources may also address the
heavy demand for healthcare
services and possibly improve outcomes (
Office of Disease Prevention and Health
Promotion
, 2006).

5




Technology

offers new functions

that may be more reliable, functional or cheaper.



Political forces
:

eHealth
tools
may improve self
-
management and adherence to proper
procedures. National policy may also embrace eHealth for coordinating health services
and promoting equality and independence of patients in addressing government health
targets, as seen in the UK.

Public policy also f
avors increasing responsibility of
consumers in managing their own health (
Office of Disease Prevention and Health
Promotion
, 2006).


eHealth applications are driven by a number of stakeholders. There are examples of eHealth
initiatives driven by citizen
-
patients, professionals, and national and regional health networks

(Silber, 2004)
.

Sometimes these stakeholders come together in an integrated service.
A
prominent example
is the
multi
-
channel eHealth service network
in the
UK
:

NHS Direct Online
-

http://www.nhsdirect.nhs.uk/index.aspx

(Gann, 2004).
In this service, patients have access via
telephone, Internet or interactive television
to
health information services provided by
professionals at the
public health service.


Increasingly, there is worldwide recognition that information and communication technology may
improve healthcare effectiveness and efficiency (
Institute of Medicine, 2001 cited in Pagliari,
2005
). National strategies have been for
med to develop the health information infrastructures in
North America, Europe and Australia (
references 2 through
5

cited in Pagliari, 2005
). For
instance, the UK National Programme for Information Technology (now called Connecting for
Health) is develop
ing a national information strategy for health.


Towards the promotion of eHealth, research has examined factors towards design and
dissemination. In the US, the Office of Disease Prevention and Health Promotion of the federal
government conducted a compr
ehensive review (2006) on consumer eHealth tools. Their goal
was to identify and analyze the critical factors in expanding the reach and impact of these tools
for a diverse population. This project was seen as a contribution towards eliminating health
di
sparities and improving health literacy. The study identified user characteristics important
towards the effective design, dissemination and use of eHealth tools for diverse populations,
which include: languages spoken; socioeconomic position; disabilitie
s; age, development and
role issues; interest in health information; and attitudes towards privacy and protection of
personal health information. These factors reflect the abilities of individuals to have the access,
ability and interest in using eHealth
tools.


Strategies for expanding the reach and impact of eHealth tools were also recommended in the
study by the Office of Disease Prevention and Health Promotion (2006). The report
recommended the following:



Provide access and training to underserved com
munities by using existing community
infrastructure, such as libraries and community technology and community
-
based
organizations



Develop statewide strategies that involve multiple partners



Reach out to target audiences



Support research addressing diverse
audiences


There are noted international efforts for promoting consumer eHealth. In the European Union,
major projects have sought to identify prioritizes and to strategize towards advancing eHealth
across Europe. For example, the eHealth ERA team on beh
alf of the European Commission,
Information Society and Media Directorate General has studied the possibilities and means of a
“smart European health space” (
eHealth ERA, 2007
). In the international realm, a global policy
6


for eHealth has been developed by

the World Health Organization: the Global Observation for
eHealth (GOe) (WHA, 58.18). This sets out global initiatives for championing eHealth
development worldwide.

5.

A
dvantages of eHealth

5.1.

General advantages of information and communication
technology for

eHealth

eHealth
is viewed as
a promising tool

by health researchers and professionals, particularly for
the potential of information and communication technologies to improve health and the
healthcare system (
Alvarez, 2002 cited in Oh et al., 2005
). Some

believe these technologies
will be promising in supporting health behavior change and chronic disease management and
prevention (Ahern et al., 2006). For family practice, researchers purport that interactive
computer technologies may address barriers to
lifestyle counseling, such as lack of time, poor
organization of information, cost of intervention, and concern about patient reactions (Glasgow
et al., 1999). Computer technologies may then address these impediments through organizing
information and app
ointments, assessing user needs, and providing training and education in an
automated manner. Furthermore, information and communication technologies may also
provide distributed access to health knowledge and reduce geographical barriers through
electron
ic as well as wireless connectivity (Iluyemi, 2007).


Some particular

advantages of information and communication technology for healthcare

are
listed in
Table
1
:


Table
1
. Advantages of information and co
mmunication technology for healthcare



Convenience and ease of use



Provide
emotional support

(especially from peers) (e.g., online discussion boards,
email)



Objectivity

and
anonymity



Widespread applicability



Telemedicine

for rural and underserved population
s



Search

and
personalized

display capabilities

-

identified by Glasgow et al. (1999) for family practice and lifestyle counseling



Instantaneous interactivity
: immediate feedback through automated responses



Convenience
: eliminates time restrictions on acce
ss to intervention and educational
materials



Appeal
: younger audience members have reported greater preference for computer
delivered information (Fotheringham, Wonnacott and Owen, 1999 cited in Fotheringham
et al., 2000)



Flexibility
: users may have access

to services where and when they have access



Individual
tailoring



Automated data collection



Credible simulations
: virtual environments could be used for role
-
playing and practicing
skills in simulated environments



Openness of communication
: responses to se
nsitive questions may be more open
when interacting with computers as opposed to other people directly (Robinson et al.,
1998 cited in Fotheringham et al., 2000)



Multimedia interfaces
: audio and video capabilities may reduce the literacy skills
7


required by

users

-

identified by Fotheringham et al. (2000) for Internet strategies for preventive medicine

5.2.

Advantages of the Internet for eHealth

It is useful to explore the advantages of the Internet for eHealth, since this modality was the first
instantiation of

eHealth programming (Strecher, 2007) and many of these features extend to
other information technologies. The following are advantages identified in a review by Strecher
(2007):



Reach
: large number of people can be reached for relatively low costs; the r
apid
increase in Internet use, particularly for health interests, attests to this potential (Bensley
et al., 2004)



Many people use the Internet
: In 2005, over 78% of adults in the US have web access,
with the largest increases in Intenret access among low
-
income and older Americans
(Center for the Digital Future, 2005 cited in Strecher, 2007). Also, 79% of respondents
in an Internet use survey reported searching for health information (representing roughly
95 million Americans) (Fox, 2005 cited in Streche
r, 2007).



A preferred resource
:

For example, in a study examining health information
preferences, the Internet was cited as a source used by 40% of breast cancer patients in
the first 16 months after diagnosis (Sutherland et al., 2003 cited in Strecher, 20
07). It
was also found that the Internet was used more frequently than other resources such as
books, videos, volunteers, support groups and telephone information services.



Convenience
:

93% of online health information seekers report the importance of
obt
aining information at any hour (Rainie and Packel, 2001 cited in Strecher, 2007).



Impersonal qualities
: The Internet may provide anonymity and prevent the discomfort
of speaking with human health professionals (
Frisby et al., 2002 cited in Strecher, 2007)
.

This may elicit openness and honesty among respondents to potentially embarrassing
and sensitive questions (Kissinger et al., 1999; Locke et al., 1992; Gribble et al., 2000 all
cited in Strecher, 2007)



Preferred for data collection
: computer
-
based system
s are preferred to paper
-
based
questionnaires (Bernhardt et al., 2001; Paperny et al., 1990 all cited in Strecher, 2007).



Interactivity
: The Internet offers four types:

o

user navigation, i.e., picking and choosing in a virtual information environment)

o

coll
aborative filters, i.e., discovering what others like you are doing

o

expert systems, i.e., automated systems that collect user characteristics and then
provide feedback and messages tailored to the users’ needs


these systems are
based on algorithms reflec
ting the standards of a human expert (Velicer, 1993
cited in Strecher, 2007)

o

human
-
to
-
human interaction: the Internet is a channel for people to meet with
other people and share information in online support groups (Brennan and Fink,
1997 cited in Strecher
, 2007). Patients may also contact health professionals via
email.



Reduced delivery costs

for health interventions and information dissemination



Timeliness

of online access anytime of the day

8




Reduction of time, geographic and mobility barriers
(
Griffiths
et al., 2006 cited in
Strecher, 2007
)



Positive health results
have been demonstrated in randomized trials of Internet
-
based
interventions for smoking cessation, hazardous drinking, weight management, diabetes,
asthma, tinnitus, stress, anxiety and depressi
on, complicated grief, encopresis, chronic
back pain, HIV, insomnia, headache and multiple risk factors (researcher studies are
listed in (Strecher, 2007)).


Further details on the advantages and disadvantages of Internet
-
based delivery of healthcare
servi
ces and information may be found in Tate and Zabinski (2004).

5.3.

Advantages of cell phones for eHealth

This literature review will
focus on cell phones

in particular. While t
elephone
-
based health
interventions have been in existence prior to the development
and adoption

of cell phones
(Friedman, 1998), r
eaders may review
the advantages of tele
phone based interventions (Clark
et al., 2007; Bunn et al., 2005; Car and Sheikh, 2003; Studdiford et al., 1996)


nevertheless,
the advantages of cell phones for eHealt
h are similar to those for telephones.


Cell phones for eHealth have been
recognized for
their

potential
. Kaplan describes its promise
as tremendous, but not fully realized due to technical, financial and regulatory barriers (2006).
C
ell phone

usage
in
h
ealthcare
remains
in its infancy.
Consequently
,
much of the research
are
pilot

or feasibility studies, which demonstrate the potential of cell phones mostly and do not
always provide rigorous and grounded evidence of its effectiveness (Kaplan, 2006). In
addition,
much

of the effectiveness
research has

been anecdotal.


There is a
strong drive

towards

cell phone eHealth.

Firstly, there are many cell phone users


the cell phone is an information and communication technology that is widespread and
seemingly

ubiquitous

with high consumer penetration
. Worldwide in 2002, cell phone
subscribers overtook land line phone subscribers, across geographic regions, socio
-
demographic variables (e.g., gender, income, age), and economic factors (
Feldmann, 2003
cited in K
aplan, 2006
). Deploying eHealth for cell phones may therefore be convenient and
far
-
reaching
.



In addition to the general issues listed in
section
5.1
, s
ome specific advantages of cell phones
include (as identified by Kaplan

(2006)

and Boland (2007))
:



Dynamic, multi
-
way interaction

between health professional and patient

is possible
with telephone
-
based communications



Manage time constraints
:
cell phones are convenient and may engage patients in self
-
care, which may reduce th
e time demands of health providers



Anytime, anywhere access

and communication

in extensive cell phone networks
.
There is
greater freedom

from
wired
landlines and
local
geographic restrictions.



Low start
-
up cost and high social value
, even in resource
-
poor

areas. The purchase
of a cell phone is relatively cheaper than computers with online access. There is also
evidence that the digital divide for cell phones is less than that of the Internet and other
communication technologies (
Forestier et al., 2002 ci
ted in Kaplan, 2006
).



Easy to use
: cell phones may be easier for people with low levels computer skills,
relative to Internet communication.



Text messaging functionalities (SMS
: Short Message Service
)
:

o

Typically costs less than voice messaging

o


Messages m
ay reach people even when phones are switched off

9


o

Relatively silent notification, permitting conversation and message transmission
when voice conversations are
neither convenient nor

appropriate

o

Highly used, for example, in 2000, text messages in the UK hi
t 1.42 billion



Communication of simple messages and data

through voice and short text messages

6.

Disadvantages of eHealth

6.1.

Disadvantages of general information and communication
technology for eHealth

A number of p
otential disadvantages
have been identified b
y researchers:


Table
2
. Potential disadvantages of information and communication technology for eHealth


in
general



Cost (especially
the initial
investment

in the transition from traditional methods
)



Complexity for some potential

users



Rapid technological changes and any resulting incompatibilities of different applications



Potential for misinformation



Loss of confidentiality risks



Limited breadth of appeal



Social justice concerns

(Glasgow et al.,
1999)



New technologies create ne
w knowledge, more data, and new expectations and
applications

(Madani
, 2006
)



Safety and cost effectiveness is not yet clearly understood; lack of evidence



Possibility of lifestyle intrusiveness for users



Concerns about data privacy in electronic networks



Concerns of private interests in telecommunications (advertisements, private control,
lack of regulations)



Potentially worsen health disparities with digital divide issues



Potential for public
campaigns against eHealth

(Wyatt and Sullivan, 2005)



Consumer
concerns for privacy and control of health information



User requirements may not be met



Lack of accessibility for financial, geographic and structural reasons

(Office of Disease Prevention and Health Promotion, 2006)



Social and public health policy concer
ns for individuals lacking web access, particularly if
individuals rely on public spaces, such as libraries, for Internet access; this may
jeopardize the benefits of open communication, anonymity, and convenience



Set up costs may be prohibitive for health
care providers

(Fotheringham et al., 2000)


6.2.

Disadvantages of cell phones for eHealth

In
addition

to the general issues
in section
6.1
, a

number of potential disadvantages
for cell
phone technologies
have been identified by
Ka
plan (2006)
:


10


Table
3
. Potential disadvantages of cell phones for eHealth


in general



Cell phone network coverage
may intermittent
in some parts of the world,
with possible

high costs due
in remote areas



Potential

high costs: e.g.
, cell phone coverage in out
-
of
-
network locations; data
transmission costs



Low bandwidth of cell phones: text messages have a maximum of 160 characters
;
how
e
ver, the technology is rapidly changing with higher bandwidth for images, Internet
access and video
s



Difficult to conduct real
-
time interaction through text messaging as data entry may be
cumbersome on tiny keypads



Small cell phone screens may be difficult to read



Literacy concerns: e.g.,
computing

and reading difficulties



Privacy of data, communication

and services (especially in public spaces): potential for
stigmatization when others witness individuals using cell phone eHealth applications in
public



Creating a sustainable, large
-
scale cell phone eHealth service requires agreement of the
different age
ndas among different stakeholders

(see
Table
4
)



Lack of evidence on the safety and efficacy (see
section
7.4

for details)

(
Kaplan, 2006
)


Further to the difficulty of different agendas among stakehol
ders, the following table developed
by Kaplan (2006) outlines the issues.


Table
4
. Stakeholder positions for cell phone eHealth


Patient

Healthcare provider

Mobile phone
company

Focus

Individual

Individual/Care Group

Potential cl
ients

Outcome

Absence

Amelioration of
disease

Absence

Amelioration of
disease

Reduce cost of care

Product sales

Motivation

Well being through
treatment

Professionalism
through treatment.

Profit through costs
containment.

Profit through new
sales, new pro
ducts,
and marketing user
acceptance.


7.

The body of
eHealth research

What are the domains of inquiry in eHealth research? What are the issues surrounding this
exploration? This section explores these questions.

7.1.

Overview of
the
eHealth research base

The b
ulk of eHealth research centers on two issues: (1) evaluation of eHealth tools and Internet
use in the public domain; and (2) the development and evaluation of eHealth tools in research
settings (Office of Disease Prevention and Health Promotion, 2006).



In a majority of the eHealth applications research, the findings contribute towards the optimism
for eHealth. However, the research conclusions are typically not conclusive due to a lack of
11


rigorous research methodologies, such as randomized controlled
trials, and a lack of diversity in
the samples (Office of Disease Prevention and Health Promotion, 2006).


The
worldwide
research needs for eHealth tools and services have been identified in a

survey
conducted by the Global Observatory for eHealth (GOe) of

the World Health Organization
(
WHO Global Observatory for eHealth
, 2006).

Some of the actions proposed for developing
eHealth among member nations include: (1) provision of generic tools (e.g., electronic health
records, drug registries, directories of h
ealth service providers), (2) access to existing tools (e.g.
directories and finding aids), (3) facilitating knowledge exchange, (4) providing eHealth
information to help nations deploy eHealth services, and (5) education of patients and health
professiona
ls of eHealth applications.

7.2.

Evaluating the technology me
dium

The technology medium of the eHealth intervention has hardly been ad
dressed. Many studies
examine

the health outcomes
of
the message delivered
by the eHealth tool;

however, little is
known abo
ut the effect of the technology itself and its related components
on
user
s

and their
health
(Kaplan, 2006).

Some questions that arise are: How does the telephone, in itself, affect
our health behavior? Do certain technologies make healthy lifestyle choic
es more amenable to
adoption?


7.3.

Usage
-
based evaluation

The evaluation of eHealth usage can be organized by the following five domains
developed by
the
Office of Disease P
revention and Health Promotion (
2006)
:

1.

Access

2.

Availability

3.

Appropriateness

4.

Acceptabilit
y

5.

Applicability


The following table defines these domains and some of the research issues

identified by the
Office of Disease Prevention and Health Promotion (2006)
.


Table
5
.
Domains of eHealth inquiry

Domain of inquiry

Definiti
on/Sample questions

Issues

Access

Uptake and use of eHealth tools.


How many p
eople know about
eHealth tools?

How many are employing these
tools?



Research bias
towards

individuals with easy Internet
access and functional levels of
computer and technology
skills.



Diffusion and dissemination.

Availability

Examines meaningful access,
that is having the tools people
want and need.

Raises issues
about
information
seeking

styles
and other personal
characteristics

shaping eHealth use
.

Appropriateness

The fit be
tween user and
the tool
.


The suitability for
user needs and
characteristics (e.g., cultural,
literacy and technological needs


Cultural relevance



User perceptions on credibility,
content, quality and readability.

12


of diverse users).

Acceptability

Whether p
eople find the tools
satisfactory



E慳a of 畳u



S慴楳f慣瑩an



U獡se 潶敲etime



U獡sility

A灰li捡cility

Utility 慮搠潵d捯浥猠of eH敡lt栠
t潯ls

Eff散t猠潮 t桥 f潬l潷i湧:



K湯wl敤g攠慮搠楮f潲m慴a潮
湥敤n



Attit畤敳 慮搠扥diefs me摩慴楮g
扥桡vi潲o捨c湧e

(e.g. 獥lf
-
e
ffi捡捹, m潴楶慴楯測 i湴n湴楯測n
數灥捴慴楯湳Ⱐ潰timism)



S潣o慬 獵s灯rt



D散e獩潮 獵s灯rt



H敡lt栠扥桡vi潲猠(慤桥r敮捥Ⱐ
摩整e 灨y獩捡c 慣瑩aity, risky
扥桡vi潲o



H敡lt栠潵h捯m敳



N敧慴楶攠潵e捯m敳



T桥 i獳略 of 效敡lth 畳uge 捡c 扥 數慭楮敤 from t桥 摩ff敲敮t

灥r獰sctiv敳e th攠
獴ak敨潬摥rs.


Table
6
.
Potential eHealth value propositions for major stakeholders

Stakeholder

Benefits Sought From Consumer e
-
Health

Consumers (e.g., patients, informal
caregivers, information intermediarie
s)



Private, 24/7 access to resources



Expanded choice and autonomy



New forms of social support



Possibility of better health



More efficient record management



Lower cost healthcare services



Avoidance of duplication of services

Consumer advocac
y and voluntary
health organizations (e.g., AARP,
American Cancer Society)



Greater capacity for health management and
education for constituents



New communication channels



More efficient service to constituents

Employers, healthcare purchasers,
and
third
-
party payers



Healthier employees more capable of health
management



Lower healthcare costs

Community
-
based organizations



Constituents with greater capacity for health
management and well
-
being



Healthier communities



Lower cost healthcare se
rvices

13


Clinicians



Gr敡ter effi捩敮捹



B整t敲 捯cm畮i捡瑩cn



M潲攠慤桥r敮t 慮d 獡瑩sfi敤 灡ti敮ts

H敡lt档hr攠erg慮iz慴楯湳



M潲攠灡ti敮t 獥sf
-
捡牥 慮搠桥慬t栠m慮agem敮t



䱯w敲e慤mi湩獴r慴楶攠e潳瑳



Im灲潶敤 q畡lity 慮搠d慴楥湴n潵t捯m敳

P畢li挠桥a
lt栠灲o杲慭s



A 桥慬t桩敲 灯灵l慴楯渠m潲o 捡c慢l攠ef 獥sf
-
捡r攠慮搠
l敳猠慴 ris欠for 慶潩摡扬攠摩獥s獥

e
-
H敡lt栠摥h敬潰敲e



S畳瑡u湥搠d獥f e
-
桥alt栠灲潤畣ts



N敷 獯sr捥猠cf 獵s灯rt f潲 灲潤畣t 摥v敬潰m敮t 慮d
敶慬畡ti潮

I湤畳ury 慮搠捯mmer捥



N敷 慤
v敲ei獩湧 v敨i捬敳



Wi摥r market猠f潲 灲潤畣瑳u

P潬icym慫er猠慮搠f畮摥r猠(灵扬i挠慮d
灲楶慴攩



Eff散瑩e攠e敡n猠of im灬敭敮eing programs 慮搠
灯li捩敳



C潳o
-
捯ct慩nm敮t 潲 捯獴
-
r敤畣瑩un 獴r慴agi敳



Q畡lity impr潶敭敮e 獴r慴agi敳e

C潰i敤 from (Offi捥
of Di獥s獥⁐牥s敮ti潮 慮d H敡lt栠偲hm潴楯測 ㈰〶)


A渠業灯nt慮t 慲敡 for 獴u摹 i猠捯獴c獡si湧猠慮d ret畲u 潮 i湶敳瑭敮t. It i猠灡rti捵c慲汹 r敬敶慮t
t漠桥慬t档hr攠潲g慮iz慴楯湳Ⱐi湳nr敲e, em灬潹敲猠慮搠g潶敲湭敮t (Offi捥 of Di獥s獥⁐r敶敮ti潮
慮搠䡥慬t栠h
romoti潮).

7.4.

Evidence for eHealth efficacy

E
vidence
to demonstrate eHealth’s effectiveness as a

health intervention is scarce.
Many
studies do not employ rigorous methodologies
n
or
employ
clear

and standard measurements for

health outcomes (Kaplan, 2006).
This is likely the result of the newness of the field where many
studies remain in the pilot or feasibility phase.
Thorough studies are currently underway, with
a
prime
example being Cochrane Review
s

on eHealth for
smoking cessation.


Some studies
demonst
rate no effect

of eHealth interventions
. Strecher (2007) points to “well
-
designed evaluations of well
-
conceived Interent
-
based [eHealth] interventions”

that

have found
no effect, particularly (Marks et al., 2006; Patten et al., 2006


both cited in Strech
er, 2007).



Other studies show mixed results for eHealth efficacy.
For example,
Norman et al. review
ed

(2007)

the efficicacy

of

eHealth interventions for physical activity and dietary behavior change
in
studies
published
between 2000 and 2005. Forty
-
ni
ne studies met the inclusion criteria of an
eHealth intervention using electronic technology
with
measured outcomes at baseline and
during a follow
-
up. Results found that
21 of 41 (51%)
studies were superior to
a

comparison
group (3 physical activity, 7 d
iet, 11 weight loss/physical activity and diet
). Also
,

24 studies had
indeterminate results, while 4 studies found the comparison intervention had outperformed the
eHealth
application
.


Rigorous efficacy studies for cell phone eHealth are particularly sca
rce. Kaplan notes that
“convincing evidence regarding the overall cost
-
effectiveness of mobile phone telemedicine is
still limited and good
-
quality studies are rare” (2006).
Generalizations are difficult to draw from
existing studies as different outcome

measurements are used and few employ controlled trials

(Kaplan, 2006)
.

14


8.

Types of
eHealth
functions possible with information and
communication technologies


Table
7

lists functions that eHealth applications may serve (based on (En
g, 2001), (Atkinson
and Gold, 2002)

and (Office of Disease Prevention and Health Promotion, 2006)
:


Table
7
.
eHealth functions
for general

information and communication technologies

Function

Example

Relay general or individual hea
lth information



Web pages and online databases

Enable informed decision making



Databases of examples and issues,
decision support tools,
risk assessment
and
multimedia.



These tools may illustrate

cases
, and
he
lp

the user to make decisions about
insurance

programs, healthcare
providers
, behavior

and treatments

Promote healthful behaviors
: behavior
change/prevention



Promote adoption and maintenance of
positive behaviors

(such as smoking
cessation)

through interventions,
services, and programs delivered via

ICTs
.

Promote peer information exchange and
emotional support

(online communities)



Share

information
and support among
patients and peers via online support
groups, etc.

Promote self
-
care

and management



Provide

tools, information and support
in electron
ic environments

for
achieving and maintaining healthy
behavior such as diet and exercise
.

Manage demand for health services



Delivery of health services through ICT
rather than in
-
person

Disease management



Offer m
onitoring, recordkeeping and
communication

with health
professionals in order to manage
chronic diseases (
e.g.,
transmitting vital
signs and health measurements for
remote monitoring)

Healthcare information management



Keep and manage

personal health
records in electronic environments

Health comm
unication



C
ommunicate

with health
professionals, agencies and other
supports

Remote patient monitoring



Monitoring devices (for weight, glucose
levels or blood pressure) may be linked
to communication networks
in order to

transmit patient measured readings

to
health professionals

(Forkner
-
Dunn,
2003)


15


eHealth behavior management models have been developed for deploying such applications.
Bensley et al.’s

model
(2004)
fits with established health behavior intervention models, the
Transtheoretical Model an
d the Theory of Planned Behavior.
Case studies have shown the
application of this model for several health situations: parent
-
child nutrition education program
by the US Department of Agriculture, asthma management among university staff and students,
and

HIV prevention in South African women (Bensley et al., 2004).

9.

Types of cell phone eHealth services currently provided

According to the academic research literature, c
ell phone eHealth
serve a number of functions
.
Briefly,
some of the services that have b
een deployed or piloted
include:




Behavior change interventions



Data collection and analysis



Diagnosis: transmitting cell phone pictures for teleconsulting (Massone et al., 2007)



Education



Health communication



Information sharing



Medical adherence



Medical
administration including appointment setting



Monitoring by health professional



Reminder service



Self
-
management / monitoring


In contrast, a market analysis report identified 101 uses of cell phones in healthcare (Wireless
Healthcare, 2005?). Categories o
f functions and services include:



Clinical decision making



Data collection



Diagnosis



Health recruitment and contact: e.g., locating blood donors



Medical administration: clinical, informational, etc.



Medical testing



Medical tool



Messaging/alert service for
public health



Patient monitoring



Records management



Reminders



Support for health professional



Support: peer and informational support


Other studies have examined eHealth services that may delivered using specific cell phone
features. Atun and Sittampala
m have investigated the uses and benefits of text messaging
(SMS) in health care delivery (2005) from the perspective of the health provider. Text
messaging is being used for: (1) enhancing efficiency of service delivery (through reminders and
improved co
mmunications); (2) improving diagnosis, treatment and rehabilitation of illness
(through remote services, patient monitoring, improved communications and delivering
behavioral change interventions); (3) public health initiatives, such as health interventio
ns,
contact tracing for communicable diseases and health information delivery.


Research studies on the above mentioned services

are reviewed in the following section.

16


9.1.

Review of cell phone eHealth research

Studies on cell phone eHealth services are reviewe
d in
Table
8
. Studies were selected to
provide an overview of the cell phone eHealth landscape and

to

demonstrate
the diversity and
range of services
. T
he goal is to give an overview and not
be
ing

exhaustive.


For more reviews

of research studies, please refer to Kaplan (2006), who has conducted a
review examining similar categories of uses with different research projects.


17





Table
8
.
Review of cell phone eHealth research


Usage
category

Health
condi
tion /
Disease

Intervention

Country

Audience /
Sample

Research
study

Research outcomes

Reference /
Comments

1

Behavior
change

Physical
activity

Physical activity program
on Internet and cell
phone.

Includes tailored
solutions for perceived
barriers, exerc
ise
scheduling tool, cell
phone and/or email
reminders, message
board, real
-
time
feedback.

UK

46
randomized
to test
group; 30 in
control with
no access to
system or
feedback.

Mean age =
40.4 (s.d. =
7.6)

Randomized
controlled trial.

Outcome
measures =
self
-
report of
physical
activity,
readings from
wrist
-
worn
accelerometer
that monitors
physical
activity

Test group had greater
self
-
reported intention to
exercise, higher level of
moderate physical
activity (average weekly
increase = 2h18min), and
lost more p
ercent body
fat relative to control
(statistically significant at
alpha = 0.05)

(Hurling et al.,
2007)

2

Behavior
change


Smoking
cessation

Providing advice for
quitting, nicotine patches,
self
-
help materials, and 8
proactive counseling
sessions via cell
phone.

USA


HIV
-
positive,
adult
smokers.

Control
group
received all
interventions
except for
cell phone
counselling
(n=47).

Intervention
group n=48


Assess impact
of cell phone
intervention on
hypothesized
mediators for
smoking
cessation (i.e.,
change in
d
epression,
anxiety, social
support, and
self
-
efficacy).

Measures =
the mediator
factors,
biochemically
confirmed
cessation
outcomes


Cell phone intervention
group exhibited favorable
changes in the mediator
factors, with the
exception of social
support, wh
ich was
rejected from the
mediator hypothesis.

The intervention resulted
in decreased symptoms
of distress.


(Vidrine et al.,
2006)

Comparison
between
groups
questionable:
while the
intervention
group received
cell phone call
counseling,
the control
group
did not
receive similar
counseling.


18



Usage
category

Health
condi
tion /
Disease

Intervention

Country

Audience /
Sample

Research
study

Research outcomes

Reference /
Comments

3

Adherence


Medication
adherence
for HIV


Healthcare professionals
placed cell phone call
reminders for medication
adherence.

Youth were provided with
free cell phones.


USA


HIV
-
infected
young adults
(16
-
24 years
ol
d)
beginning
HAART drug
regimen

5
participants
completed
the study


Pilot program

Daily calls for
initial 4 weeks;
frequency was
then tapered.

Perceived
intrusiveness
or helpfulness
of service,
missed
medication
doses, and
laboratory
tests (viral
load) wer
e
assessed at 4
week intervals
for 12 weeks,
with a follow
-
up at week 24.


Most participants found
service helpful, with an
acceptable level of
intrusion.

Calls were deemed
annoying initially by
patients, but less
annoying by week 12.

Some participants
app
reciated the calls,
especially for
opportunities to ask
health questions.

Viral suppression waned
for majority of patients;
researchers believe 12
-
week intervention is not
sufficiently long.


(Puccio et al.,
2006)


4

Self
-
management/

monitoring

Health
com
munication


Cardiac
dysfunctions


Blood pressure, weight
measurements, and
medication dosage data
transmitted via mobile
phone for telemonitoring.

Physician receives email
to alert out
-
of
-
range
conditions.


Austria


14 patients
with chronic
heart failure

6

patients
with
hypertension


Monitoring for
90 day period.

Examining
reliability,
acceptability
and feasibility
of system.

Survey
questionnaire.


Over 90 day period,
average submissions per
patent was 102 (s.d 43).

On average, 83% (s.d.
22) of submissions
were
successfully transmitted.

Stability and accessibility
both above 98%.

From survey on
experiences (n=18), high
acceptance of program,
increased awareness
experienced, and interest
in continuing program at
personal expense.


(Scherr et al.,
2006)


19



Usage
category

Health
condi
tion /
Disease

Intervention

Country

Audience /
Sample

Research
study

Research outcomes

Reference /
Comments

5

Se
lf
-
management/

monitoring

Health
communication


Diabetes

Hypertensio
n


Blood pressure monitor
and glucometer linked to
cell phone (Bluetooth
-
enabled) transmits data
to central data repository
where clinical rules are
applied and alerts
generated.

Alerts se
nt to physician
and to the patient (via
text and phone
messages).


Canada


Focus
groups: 24
type II
diabetics
with
hypertension
, 18 family
physicians

Pilot study:
32 diabetics
with
hypertension
completed
study


Focus groups
to develop
system.

Pilot study o
f
system.


From pilot study,
significant improvement
in blood pressure
measures at ambulatory
(24 hour) and 2
-
week
intervals (statistically
significant at p < 0.01).

Focus groups established
design principles for
system.


(Trudel et al.,
2007)

Authors note

need for
clinical trial to
confirm results
and to
examine
adherence
issues.


6

Information
sharing

Self
-
monitoring/

management


Diabetes


Transfer blood glucose
readings from child's
monitor to parent's
mobile phone.


Norway


15 children
(9
-
15 y.o.)
with

type 1
diabetes

Their
parents
(n=30)


Parent and
child
experiences
and
satisfaction
were collected
via
questionnaires
.

Interviews
(with 9 of the
parents).


Parents valued sense of
reassurance.

System easily integrated
into everyday life.

Reduction of par
ental
intrusion for children who
monitored regularly.

Increased
nagging/reminders by
parents for children who
measured irregularly
-

possibly leading to
conflict.

Parents expressed
concern about age
-
appropriateness
(especially for
adolescents) and
children
's independence
and sense of
responsibility.


(Gammon et
al., 2005)


20



Usage
category

Health
condi
tion /
Disease

Intervention

Country

Audience /
Sample

Research
study

Research outcomes

Reference /
Comments

7

Self
-
management/

monitoring


Diabetes


Patients transmit daily
measurements including
glucose levels to server.

Text message feedback
to acknowledge or
provide help or warning
messages

of health
conditions.

Calculates and sends
health measures
(glycosylated
haemoglobin result) to
patient.


Spain


23 diabetic
patients (18
y.o. and
over).


User
satisfaction
survey.

System use
log analysis.

Cost analysis.


Patients sent an average
of 33 me
ssages/month.

Overall user satisfaction
(26% survey response
rate only).

Concerns about cell
phone plan costs.

Projected cost to
diabetes manager is
€3/month.


(Ferrer
-
Roca
et al., 2004)


8

Self
-
management/

monitoring

Education


Diabetes


Patients send se
lf
-
monitored blood glucose
levels and drug
information to an Internet
server system via wired
connection or cell phone.

Nurse reviews patient
records and data to send
weekly recommendations
for self
-
management via
SMS or Internet.


South
Korea


25
randomiz
ed
patients to
intervention
group (mean
age = 46.8).

26
randomized
patients to
control
(mean age =
47.5).


Comparison
between
intervention
and control
groups.

Pre
-
/post
-
test.

Outcome
measurement
= blood
glucose level
indicators


Intervention group had
impr
oved blood glucose
concentrations, relative to
control group and
statistically significant at
p < 0.05.

Reporting of results was
unclear.


(Kim, 2006)


21



Usage
category

Health
condi
tion /
Disease

Intervention

Country

Audience /
Sample

Research
study

Research outcomes

Reference /
Comments

9

Self
-
management/

monitoring


Calorie
monitoring
for weight
managemen
t


PmEB, cell phone
application f
or self
-
monitoring caloric
balance in real time.


USA


Varied.

Feasibility
study with
15 clinically
overweight
or obese
individuals
(18 years
and older)


Iterative R&D
methodology

Usability study

Preliminary
feasibility
study
measuring
compliance
and
satis
faction
with 15
participants
randomized
into 3 groups
(paper diary,
PmEB with 1
daily prompt,
PmEB with 3
daily prompts)


Feasibility study results
follows.

High scores for PmEB
usability, compliance and
satisfaction.

PmEB scored as highly if
not better th
an paper
group in most all
categories (lacking tests
of statistical significance).

From thematic analysis of
qualitative interviews:
PmEB is motivating,
helpful for developing
weight management
practices, convenient,
easy to use.

Negative comments =
food e
ntry was
challenging, disliked
prompts


(Tsai et al.,
2006)


22



Usage
category

Health
condi
tion /
Disease

Intervention

Country

Audience /
Sample

Research
study

Research outcomes

Reference /
Comments

10

Self
-
management/

monitoring


Asthma


Cell phone monitoring
system.

Symptoms and peak
flows transmitted to
central server; immediate
feedback provided for
control and appropriate
actions.


UK


Focus group
and trial
interventions
conducted
with a mix of
34 adults
and
teenagers
with asthma
and 14
asthma
nurses and
physicians.


Focus group
discussion
after a
demonstration
of the
technology.

In
-
depth
interviews of 9
participants
before and
after a
4
-
week
trial of the
system.


Participants felt the
technology may facilitate
guided self
-
management;
however, dependence on
professional or
technological support
may develop.

Provides confidence for
new patients to
understand and control
their asthma.

Conc
erns that increased
dependence may be
unhelpful for long term
self
-
management.

Participants appreciated
the on
-
going record
generated for
consultations.


(Pinnock et al.,
2007)

In a related
questionnaire
survey on
professional
and patient
attitudes to the
technology,
results
exhibited
minority
interest, with
th
e
enthusiastic
minority
concerned

about clinical
benefit
s
,
impact on self
-
management
,

and workload
and costs
(Pinnock et al.,
2006).


23



Usage
category

Health
condi
tion /
Disease

Intervention

Country

Audience /
Sample

Research
study

Research outcomes

Reference /
Comments

11

Data collection
and analysis

Health
information


Asthma


Elect
ronic peak flow
meter linked to a cell
phone, where symptoms
may be transmitted and
stored on a server.

System includes an
interactive service for
reviewing their readings
and finding data on
weather conditions (that
affect asthma conditions).


UK


10 asth
ma
patients, 2
research
staff
members


Qualitative
interviews on
participants'
experiences
with the
system.


Strengths = easy to use,
fast, saved time,
improved awareness of
asthma conditions,
identifies problems,
facilitate virtual
communication.

Weakness
es =
dissatisfaction and
frustration with
technology interface and
failures.

Future development =
more system feedback
on conditions, training
and support for staff.


(Cleland et al.,
2007)


12

Data collection
and analysis


Asthma


Electronic peak flow
me
ter linked to a cell
phone.

Software transmits
readings to server with
feedback as an asthma
trend analysis.


UK


38 asthma
patients
under 18 yo.
and 53
patients over
18 yo.


Observational
study over 9
months, with
compliance to
technology
use as primary
o
utcome for
analysis.

Questionnaire
follow
-
up.


Patients sent peak flow
readings once a day 68%
of the time and twice a
day 55% of the time.

From 46 participants who
responded follow
-
up
questionnaire, 74% felt
system improved self
-
management and 69%
were sa
tisfied or very
satisfied.

Positive features
identified = increased
awareness, increased
information, feedback,
ease of use


(Ryan et al.,
2005)


24



Usage
category

Health
condi
tion /
Disease

Intervention

Country

Audience /
Sample

Research
study

Research outcomes

Reference /
Comments

13

Mo
nitoring by
health
professional

Data collection


Cancer


WHOMS
-

Wireless
Health Outcomes
Monitoring Sys
tem, an
Internet
-
based system
that delivers structured
questionnaires via cell
phone to patients for self
-
reported outcomes on
symptoms and quality
-
of
-
life.

Survey response via cell
phone keypad entry.

Questionnaire results
delivered to health
professional
s for patient
monitoring.


Italy


97 cancer
inpatients


Patients asked
to complete a
ten
-
item
questionnaire
regarding
symptoms.


Only 56 of the patients
agreed to try cell phone
survey.

61% of responses were
complete.

Patients who did not
participate were
typically
older, received less
education, and less
familiar with new
information and
communication
technologies.


(Bielli et al.,
2004)


25



Usage
category

Health
condi
tion /
Disease

Intervention

Country

Audience /
Sample

Research
study

Research outcomes

Reference /
Comments

14

Health
communication


Sexual
health test
results


Text message delivery of
test results for
Chlamydia
trachomatis

i
nfection.


UK

London
area


Patients
attending a
sexual
health clinic


For untreated
and infected
individuals, a
comparison of
the time to
treatment
between the
intervention
group and the
control group
-

the latter were
notified by
standard
methods (clinic
re
-
attendance,
results phone
line).

Measures =
demographic
data,
attendance
data, staff
hours to
deploy service


Individuals with CT
infection and who employ
the text message
notification service are
contacted and receive
treatment sooner.

Median time to t
reatment
= 8.5 days vs 15.0 days
for control group;
statistically significant
difference (p=0.005)


(Menon
-
Johansson et
al., 2006)


26



Usage
category

Health
condi
tion /
Disease

Intervention

Country

Audience /
Sample

Research
study

Research outcomes

Reference /
Comments

15

Reminder
service


Appointment
notification


Text message reminders
of forthcoming medical
appointments.


UK


Patients at

outpatient
clinics of a
major
children's
teaching
hospital.


Identify impact
on reducing
"no
-
shows" at
medical
appointments.

Compared
"no
-
show" rate
between
patients who
receive text
message
reminders and
those who do
not.


Text message is effective
for s
ending last minute
reminder to patients.

Modest impact for "partial
booking" appointments.

Limited coverage,
particularly among the
elderly.

Cheaper, more reliable
and timely than sending
paper letters.


(Milne et al.,
2006)

In article
background,
descript
ion of
other text
message
services at
different
hospitals that
were
terminated due
to operational
difficulties.







27


9.2.

Images of cell phone eHealth
applications

9.2.1.

Behavior change


physical activity


Figure
1

Weekly schedule for pl
anning physical activity

(on an Internet
-
based interface)

(Hurling et al., 2007)


28


9.2.2.

Data collection, data analysis and health information


asthma


Figure
2

The Piko meter, connecting cable and Motorola V600 phone

(Cleland et al.,
2007)



Figure
3

(
a
) Screen shot of mobile phone demonstrating the previous two weeks’ peak flow

readings.

(
b
) Final screen on conclusion of the session


(Cleland et al., 2007)

29


9.2.3.

Self
-
management/monitoring



a
sthma


Figure
4

Example of a mobile phone based monitoring system (E
-
san Ltd: mmO2).

(Pinnock et al., 2007)



Figure
5

Patient enters diary symptoms on cell phone.


(Boland et al., 2007)


30



Figure
6

Pa
tient receives instant feedback and action plan.

(Boland et al., 2007)


Images from Boland’s description of a cell phone application for asthma that includes features
for (2007):



Personalized diary



Medical regiment information on schedules



Automated system

reminders and tailored messages



Action plans



Summary and detailed patient data



Web portal with provider drill down capability



Exception report son noncompliant patients

31


9.2.4.

Self
-
management/monitoring


diabetes and hypertension


Figure
7

Mobile phone based remote patient monitoring system

(Trudel et al., 2007)


9.2.5.

Self
-
management/monitoring



weight management


Figure
8

Screenshots of the PmEB mobile phone client. (a) is the main application menu. (b) is the cur
rent
caloric balance page. (c) is the meal selection page. (d) is the history page.

(Tsai et al., 2006)


32


9.2.6.

Monitoring by health professional and data collection


cancer


Figure
9

Questionnaire compilation using a mobile phone. The
question is displayed on the left, and the
answer set associated with each question is displayed on the right

(Bielli et al., 2004)


9.2.7.

Medical administration


appointment making


Figure
10

Intelligent SMS


Reminding of appointmen
t

(Nokia, 2005)


33



Figure
11

Intelligent SMS


Rescheduling an appointment

(Nokia, 2005)



Figure
12

Intelligent SMS


Confirming appointment

(Nokia, 2005)

9.2.8.

Medication management


34



Figure
13

A
n internet
-
based system and a novel mobile home based devic
e

for the management of

medication
-

with drug compliance reminder via
cell
phone, medical reminder and medication
compliance monitoring
. Drug
compliance

reminder

via cell phone
: (a) m
edication reminder and
(b) medication compliance monitoring

(Nugent et al., 2007)

9.2.9.

Diagnosis and teleconsulting


skin cancer


Figure
14

This dermoscopic image of a pigmented skin lesion has been captured applying the cellular
phon
e on a pocket epiluminescence microscopy device.

(Massone et al., 2007)

35



10.

Issues surrounding cell phone eHealth

10.1.

Mobile healthcare

Mobile healthcare (also known as mHealth) is a class of technologies that include
s

cell phone
eHealth as a subset. mHealth
is
defined as the combination of mobile and wireless
technologies with eHealth (Iluyemi, 2007). It may include the integration of medical sensors and
mobile computing into a medical system (Madani,
2006
).

The advantages include providing real
time patient c
are with fewer limits on time and geography through mobile technology. It is
important to recognize that cell phones are simply one of many options for portable information
and communication technologies in healthcare.

10.2.

Technology divide

Information and co
mmunication t
echnology
in health
care may
hinder those
who lack
access to
the technology. This “divide”

could reinforce the barriers to medical knowledge and information,
which typically fall along social, financial and
other
involuntary
lines
(Kaplan, 200
6).

In addition,
those without access to computer technologies are typically underserved in the healthcare
system and experience the greatest health disparities (
Eng et al., 1998
).


The

eHealth technology divide may fall along two classes: (1) hardware, w
hich includes the
machines and the communications network, such as the Internet; and (2)
software and content,
such as online support groups and health information (Viswanath and Kreuter, 2007).

Hardware
issues affect both patien
ts and healthcare provider
s, who

may not have the resources to invest
in a new eHealth system.

Software and content barriers may extend to even individuals who
have access to the eHealth technology. For example, some user groups may have cultural
barriers for understanding health

information, or find the usability of web pages and other
content difficult.


While some research indicates that seniors and many minority groups are one of the quickest
-
growing segment of Internet users (
references
22,

23,

and
25

cited in Forkner
-
Dunn, 2
003
),
barriers may
also emerge as the inability or lack of skills to use technology. Forkner
-
Dunn
(2003) and Eng (2001) encourage the study of these and other barriers in for the successful
design and deployment of eHealth
, including: literacy, disabiliti
es, and cultural factors.



10.3.

He
alth disparities and eHealth

Disparities in health and healthcare access are increasingly prominent concerns
for

research
and practice (Gibbons, 2005).


There is little consensus behind the causes of these disparities, but m
any find it is related to
socio
-
cultural, behavioral, economic, environmental, biological or societal factors (Gibbons,
2005)
.
While these social and physical factors are increasingly a focus in the advancing
research, the role of the information environm
ent has been neglected in the scientific inquiry
(Viswanath and Kreuter, 2007).



eHealth has been proposed to ameliorate health disparities. Authorities have suggested greater
research and investment in information technology (Gibbons, 2005)
.
Such equi
pment may
overcome health disparities through several roles

technology can play

(Gibbons, 2005)
:

36




Improve health communication. The Institute of Medicine has called for initiatives that
may enhance patient
-
provider communication, trust and cultural appropr
iateness of care
(
Smedley et al., 2003 cited in Gibbons, 2005
).



Deliver interventions such as behavior change support. Time and geographic barriers
may be overcome through telecommunications and computer automation.



Improve access to quality information.

The real
-
time and anywhere access of electronic
of information may be more easily accessible than traditional, print materials.


Concerned that eHealth advances will help “eliminate, not exacerbate” health disparities,
Viswanath and Kretuer (2007) recomme
nd a research agenda that:



Identifies and articulates specific disparity issues



Enhances survey sampling and measure to better understand and address disparities in
eHealth research



Critically examines eHealth and communications policies that could affect
health
disparities


Issues of social justice and disparities have been addressed in codes of ethics for eHealth
(Wyatt and Sullivan, 2005).


10.4.

eHealth literacy

eHealth literacy is “the ability to seek, find, understand, and appraise health information from
e
lectronic sources and apply the knowledge gained to addressing or solving a health problem”
(Norman and Skinner, 2006). There are six literacy types that form the foundational skills for
the optimum eHealth experience

(Norman and Skinner, 2006)
:

1.

tradition
al literacy and numeracy

2.

media literacy

3.

information literacy

4.

computer literacy

5.

science literacy

6.

health literacy

The first three skills address analytical skills
while
the final three are context
-
specific skills,
which
typically require more specialized tra
ining. Norman and Skinner also identify the specific
problems for each skill set as well as the potential resources to address them (2006).


H
ealth literacy is “the degree to which individuals have the capacity to obtain, process and
understand basic heal
th information and services needed to make appropriate health decisions”
(Office of Disease Prevention and Health Promotion
, 2006
)
.


There is a measurement tool to measure eHealth literacy. eHeals, the eHealth Literacy Scale,
was designed to (1) assess
self
-
perceived skills at using information technology for health, and
(2) to determine the fit of eHealth programs with consumers (Norman and Skinner, 2006,
eHeals).
The scale consists of an eight item measure that evaluates the consumer’s
knowledge, comf
ort and perceived skills at using electronic health information for health issues


and this scale has been empirically validated with a youth population (Norman and Skinner,
2006).

37


11.

Future research

From this literature

review, categories of the gaps,
probl
ems
and needs
in cell phone eHealth
are listed in
Table
9

along with the related research questions.

38



Table
9
.
Areas for future research

Gaps /
problems

/ needs

Research
topics

Support by
researchers

App
ropriate use of cell
phone eHealth



Identifying critical components
and optimal conditions for use

(Office of Disease
Prevention and
Health Promotion,
2006)

Civil liberties: privacy
infringement



Protecting privacy of electronic
health information



Public po
licy development

(Office of Disease
Prevention and
Health Promotion,
2006)

Effectiveness of cell phone
eHealth



Cost effectiveness



Health outcomes



Evaluation



Usability

(Kaplan, 2006)

(Office of Disease
Prevention and
Health Promotion,
2006)

Effects on the

patient and
the provider



Stakeholder analyses



Ethnographic studies

(Oh et al., 2005)

Evaluation methods and
challenges



Addressing concerns regarding
the sensitivity, validity and
reliability of outcome measures



Application of rigorous
methodologies such
as
controlled trials



Diverse sampling



More qualtitative studies

(Ahern et al., 2006)

Health disparities



Addressing gaps in healthcare
access

(Ahern et al., 2006)

Health information behavior



Information use, processing,
sharing and control with
technology

(Jones et al., 2005)

Inconclusive studies and
mixed results



Systematic reviews and meta
-
analyses



Continued research

(Kaplan, 2006)

Poor understanding of the
user’s experience



User needs, perceptions,
experiences, characteristics
and expectations

(Strech
er, 2007)

Regulation and policies
supportive of eHealth



Review of telecommunications
and healthcare policies

(Kaplan, 2006)

Technical quality



Linking research with system
development



Interoperability

(Office of Disease
Prevention and
Health Promotion,
20
06)

(Ahern et al., 2006)

39


Gaps /
problems

/ needs

Research
topics

Support by
researchers

Thoughtful and participatory
eHealth development by
stakeholders



Stak敨潬摥r 湥敤s, 灲楯riti敳e
慮搠灥d獰sctiv敳



Diff畳u潮 慮搠摩獳smi湡ti潮 of
t散e湯l潧y



B畩l摩湧 vi慢ility 慮搠
獵獴慩湡扩lity



Q畡lity of 效敡lth t潯ls 慮搠
獥牶i捥c



Evi摥湣n
-
扡獥s 獴rategi敳



U獥爠i湶潬v敭敮e



I湴n杲慴i潮 of 效敡lth wit栠潴桥r
桥慬t栠楮f潲mati捳c
摥v敬潰m敮ts



C潮獥s獵猠慮搠獴慮摡rdiz慴楯n



Multi
-
摩獣s灬i湡ry 捯cl慢or慴楯n

(K慰l慮, ㈰〶)

(Offi捥 of Di獥s獥s
Pr敶敮ti潮 慮搠
H敡lt栠偲hm潴楯測
㈰〶2

(P慧li慲椠a
t 慬., ㈰〵)

(A桥r渠nt 慬., ㈰〶)

(Stre捨cr, ㈰〷)


12.

References


Ahern, D.K., Kreslake, J.M. & Phalen, J.M. 2006, "What is eHealth (6): Perspectives on the
evolution of eHealth research", Journal of Medical Internet Research, vol. 8, no. 1.


Atkinson, N.L.

& Gold, R.S. 2002, "The promise and challenge of eHealth interventions",
American Journal of Health Behavior, vol. 26, no. 6, pp. 494
-
503.


Bensley, R.J., Mercer, N., Brusk, J.J., Underhile, R., Rivas, J., Anderson, J., Kelleher, D.,
Lupella, M. & de Jage
r, A.C. 2004, "The eHealth Behavior Management Model: a stage
-
based
approach to behavior change and management", Preventing chronic disease, vol. 1, no. 4.


Bielli, E., Carminati, F., La Capra, S., Lina, M., Brunelli, C. & Tamburini, M. 2004, "A Wireless
H
ealth Outcomes Monitoring System (WHOMS): development and field testing with cancer
patients using mobile phones", BMC medical informatics and decision making, vol. 4, pp. 7.


Boland, P. 2007, "The emerging role of cell phone technology in ambulatory care"
, Journal of
Ambulatory Care Management, vol. 30, no. 2, pp. 126
-
133.


Bunn, F., Byrne, G. & Kendall, S. 2005, "The effects of telephone consultation and triage on
healthcare use and patient satisfaction: a systematic review", The British journal of genera
l
practice : the journal of the Royal College of General Practitioners, vol. 55, no. 521, pp. 956
-
961.


Car, J. & Sheikh, A. 2003, "Telephone consultations", BMJ (Clinical research ed.), vol. 326, no.
7396, pp. 966
-
969.


Clark, R.A., Inglis, S.C., McAliste
r, F.A., Cleland, J.G. & Stewart, S. 2007, "Telemonitoring or
structured telephone support programmes for patients with chronic heart failure: systematic
review and meta
-
analysis", BMJ (Clinical research ed.), vol. 334, no. 7600, pp. 942.

40



Cleland, J., Cal
dow, J. & Ryan, D. 2007, "A qualitative study of the attitudes of patients and staff
to the use of mobile phone technology for recording and gathering asthma data", Journal of
telemedicine and telecare, vol. 13, no. 2, pp. 85
-
89.


eHealth ERA 2007, eHealth

priorities and strategies in European countries, eHealth ERA,
Brussels.


Eng, T.R. 2001, The eHealth landscape: a terrain map of emerging information and
communication technologies in health and health care, The Robert Wood Johnson Foundation,
Princeton,
NJ.


Eng, T.R., Maxfield, A., Patrick, K., Deering, M.J., Ratzan, S.C. & Gustafson, D.H. 1998,
"Access to health information and support: a public highway or a private road?", JAMA : the
journal of the American Medical Association, vol. 280, no. 15, pp. 13
71
-
1375.


Eysenbach, G. 2001, "What is e
-
health?", Journal of medical Internet research, vol. 3, no. 2, pp.
E20.


Ferrer
-
Roca, O., Cardenas, A., Diaz
-
Cardama, A. & Pulido, P. 2004, "Mobile phone text
messaging in the management of diabetes", Journal of tel
emedicine and telecare, vol. 10, no. 5,
pp. 282
-
285.


Forkner
-
Dunn, J. 2003, "Internet
-
based patient self
-
care: the next generation of health care
delivery", Journal of medical Internet research, vol. 5, no. 2, pp. e8.


Fotheringham, M.J., Owies, D., Lesli
e, E. & Owen, N. 2000, "Interactive health communication
in preventive medicine: internet
-
based strategies in teaching and research", American Journal of
Preventive Medicine, vol. 19, no. 2, pp. 113
-
120.


Friedman, R.H. 1998, "Automated telephone conversat
ions to assess health behavior and
deliver behavioral interventions", Journal of medical systems, vol. 22, no. 2, pp. 95
-
102.


Gammon, D., Arsand, E., Walseth, O.A., Andersson, N., Jenssen, M. & Taylor, T. 2005,
"Parent
-
child interaction using a mobile and

wireless system for blood glucose monitoring",
Journal of medical Internet research, vol. 7, no. 5, pp. e57.


Gann, B. 2004, "NHS Direct Online: a multi
-
channel eHealth service", Studies in health
technology and informatics, vol. 100, pp. 164
-
168.


Gatzou
lis, L. & Iakovidis, I. 2007, "Wearable and portable eHealth systems", IEEE Engineering
in Medicine and Biology Magazine, vol. 26, no. 5, pp. 51
-
56.


Gibbons, M.C. 2005, "A historical overview of health disparities and the potential of eHealth
solutions",
Journal of Medical Internet Research, vol. 7, no. 5.


Glasgow, R.E., McKay, H.G., Boles, S.M. & Vogt, T.M. 1999, "Interactive computer technology,
behavioral science, and family practice", The Journal of family practice, vol. 48, no. 6, pp. 464
-
470.


41


Hurli
ng, R., Catt, M., Boni, M.D., Fairley, B.W., Hurst, T., Murray, P., Richardson, A. & Sodhi,
J.S. 2007, "Using internet and mobile phone technology to deliver an automated physical
activity program: randomized controlled trial", Journal of medical Internet
research, vol. 9, no. 2,
pp. e7.


Iluyemi, A. 2007, "Mobile/Wireless eHealth for health system/workers development in Africa:
opportunities for emobility ETP", 2nd Workshop on Shaping the Future of Mobile and Wireless
Communications.


Jones, R., Rogers, R.
, Roberts, J., Callaghan, L., Lindsey, L., Campbell, J., Thorogood, M.,
Wright, G., Gaunt, N., Hanks, C. & Williamson, G.R. 2005, "What is eHealth (5): A research
agenda for eHealth through stakeholder consultation and policy context review", Journal of
Me
dical Internet Research, vol. 7, no. 5.


Kaplan, W.A. 2006, "Can the ubiquitous power of mobile phones be used to improve health
outcomes in developing countries?", Globalization and health, vol. 2, pp. 9.


Kim, H.S. 2007, "A randomized controlled trial of

a nurse short
-
message service by cellular
phone for people with diabetes", International journal of nursing studies, vol. 44, no. 5, pp. 687
-
692.


Koch, S. 2006, "Meeting the challenges
--
the role of medical informatics in an ageing society",
Studies in he
alth technology and informatics, vol. 124, pp. 25
-
31.


Kollmann, A., Kastner, P., Pusch, W., Riedl, M., Ludvik, B., Scherr, D., Zweiker, R., Fruhwald, F.
& Schreier, G. 2005, "Patient centred health data acquisition using mobile phones", , pp. 606.


Madani
, K. 2006, M
-
Health project, University of Westminster, London.


Massone, C., Hofmann
-
Wellenhof, R., Ahlgrimm
-
Siess, V., Gabler, G., Ebner, C. & Peter Soyer,
H. 2007, "Melanoma screening with cellular phones", PLoS ONE, vol. 2, no. 5, pp. e483.


Menon
-
Joha
nsson, A.S., McNaught, F., Mandalia, S. & Sullivan, A.K. 2006, "Texting decreases
the time to treatment for genital Chlamydia trachomatis infection", Sexually transmitted
infections, vol. 82, no. 1, pp. 49
-
51.


Milne, R.G., Horne, M. & Torsney, B. 2006, "S
MS reminders in the UK National Health Service:
An evaluation of its impact on "no
-
shows" at Hospital Out
-
Patient Clinics", Health care
management review, vol. 31, no. 2, pp. 130
-
136.


Nokia 2005, Value of mobility in healthcare, Nokia, ?.


Norman, C.D. &
Skinner, H.A. 2006, "eHEALS: The eHealth literacy scale", Journal of Medical
Internet Research, vol. 8, no. 4.


Norman, C.D. & Skinner, H.A. 2006, "eHealth Literacy: Essential Skills for Consumer Health in a
Networked World", Journal of medical Internet re
search, vol. 8, no. 2.


Norman, G.J., Zabinski, M.F., Adams, M.A., Rosenberg, D.E., Yaroch, A.L. & Atienza, A.A.
2007, "A Review of eHealth Interventions for Physical Activity and Dietary Behavior Change",
American Journal of Preventive Medicine, vol. 33,
no. 4.

42



Nugent, C., Finlay, D., Davies, R., Mulvenna, M., Wallace, J., Paggetti, C., Tamburini, E. &
Black, N. 2007, "The next generation of mobile medication management solutions", International
Journal of Electronic Healthcare, vol. 3, no. 1, pp. 7
-
31.


Office of Disease Prevention and Health Promotion 2006,

Expanding the Reach and Impact of

Consumer e
-
Health Tools, US Department of Health and Human Services, Bethesda, MD.


Oh, H., Rizo, C., Enkin, M. & Jadad, A. 2005, "What is eHealth (3): A systematic r
eview of
published definitions", Journal of Medical Internet Research, vol. 7, no. 1.


Pagliari, C., Sloan, D., Gregor, P., Sullivan, F., Detmer, D., Kahan, J.P., Oortwijn, W. &
MacGillivray, S. 2005, "What is eHealth (4): A scoping exercise to map the fie
ld", Journal of
Medical Internet Research, vol. 7, no. 1.


Pinnock, H., Slack, R., Pagliari, C., Price, D. & Sheikh, A. 2007, "Understanding the potential
role of mobile phone
-
based monitoring on asthma self
-
management: qualitative study", Clinical
and exp
erimental allergy : journal of the British Society for Allergy and Clinical Immunology, vol.
37, no. 5, pp. 794
-
802.


Pinnock, H., Slack, R., Pagliari, C., Price, D. & Sheikh, A. 2006, "Professional and patient
attitudes to using mobile phone technology to

monitor asthma: questionnaire survey", Primary
care respiratory journal : journal of the General Practice Airways Group, vol. 15, no. 4, pp. 237
-
245.


Puccio, J.A., Belzer, M., Olson, J., Martinez, M., Salata, C., Tucker, D. & Tanaka, D. 2006, "The
use of

cell phone reminder calls for assisting HIV
-
infected adolescents and young adults to
adhere to highly active antiretroviral therapy: A pilot study", AIDS Patient Care and STDs, vol.
20, no. 6, pp. 438
-
444.


Ryan, D., Cobern, W., Wheeler, J., Price, D. & T
arassenko, L. 2005, "Mobile phone technology
in the management of asthma", Journal of telemedicine and telecare, vol. 11 Suppl 1, pp. 43
-
46.


Scherr, D., Zweiker, R., Kollmann, A., Kastner, P., Schreier, G. & Fruhwald, F.M. 2006, "Mobile
phone
-
based survei
llance of cardiac patients at home", Journal of telemedicine and telecare,
vol. 12, no. 5, pp. 255
-
261.


Silber, D. 2004, "The case for eHealth", Studies in health technology and informatics, vol. 100,
pp. 3
-
27.


Strecher, V. 2007, Internet methods for del
ivering behavioral and health
-
related interventions
(eHealth).


Studdiford, J.S.,III, Panitch, K.N., Snyderman, D.A. & Pharr, M.E. 1996, "The telephone in
primary care", Primary care, vol. 23, no. 1, pp. 83
-
102.


Tate, D.F. & Zabinski, M.F. 2004, "Computer

and Internet applications for psychological
treatment: update for clinicians", Journal of clinical psychology, vol. 60, no. 2, pp. 209
-
220.


43


Trudel, M., Cafazzo, J.A., Hamill, M., Igharas, W., Tallevi, K., Picton, P., Lam, J., Rossos, P.G.,
Easty, A.C. &
Logan, A. 2007, "A mobile phone based remote patient monitoring system for
chronic disease management", Medinfo.MEDINFO, vol. 12, no. Pt 1, pp. 167
-
171.


Tsai, C.C., Lee, G., Raab, F., Norman, G.J., Sohn, T., Griswold, W.G. & Patrick, K. 2006,
"Usability a
nd Feasibility of PmEB: A Mobile Phone Application for Monitoring Real Time Caloric
Balance", , pp. 1.


Vidrine, D.J., Arduino, R.C. & Gritz, E.R. 2006, "Impact of a cell phone intervention on mediating
mechanisms of smoking cessati
on in individuals living with HIV/AIDS", Nicotine & tobacco
research : official journal of the Society for Research on Nicotine and Tobacco, vol. 8 Suppl 1,
pp. S103
-
8.


Viswanath, K. & Kreuter, M.W. 2007, "Health Disparities, Communication Inequalities, a
nd
eHealth", American Journal of Preventive Medicine, vol. 32, no. 5.


WHO Global Observatory for eHealth 2006, eHealth tools and services: needs of the member
states, World Helath Organization, Switzerland.


Wireless Healthcare 2005?, 101 things to do wit
h a mobile phone in healthcare, Wireless
Healthcare, UK.


Wyatt, J.C. & Sullivan, F. 2005, "ABC of health informatics: eHealth and the future: Promise or
peril?", British medical journal, vol. 331, no. 7529, pp. 1391
-
1393.